The present exemplary embodiments relate to automated diagnosis of resources in production systems having multiple resources for achieving production goals. Diagnosing system performance and component status can advantageously aid in improving productivity, identifying faulty or underperforming resources, scheduling repair or maintenance, etc. Accurate diagnostics requires information about the true condition of components in the production system. Such information can be obtained directly from sensors associated with individual components and/or may be inferred from a limited number of sensor readings within the production plant using a model or other knowledge of the system structure and dynamics. However, providing complete sensor coverage for all possible system faults can be expensive or impractical in harsh production environments. Thus, a need remains for improved diagnostic techniques and systems by which the probabilities of production resources being faulty can be ascertained without requiring complete sensor coverage.